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471 results for “Neural Network (NN)”
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Research ArticleOpen accessEvery word in the titleFacial Recognition and Discovery Using Convolution Deep Learning Neural NetworkAbdel Karim Mohamed BaarehFacial recognition is a critical and well-established topic that has caught the interest of researchers across various application areas. Face detection and identification are critical components of human detection systems. Researchers in different fields used numerous techniques to recognize human faces in various positions considering several features, many results were also obtained. In this research, we aim to use a … …Journal of Computer Science, Vol. 20, Issue 11 · 22 Oct 2024 · 5,243 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleDDoS Attack Detection Using Enhanced Neural Network Algorithm in Software-Defined NetworksHema Surendrakumar Dhadhal, Paresh P KotakWith the uncommon advancement of technology and networking, the world today is totally relying on it. The most obvious drawback of this technical progress resulted in several possible dangers. A Distributed Denial of Service (DDoS) attack is one in which a large number of compromised systems work together to prevent service from being provided to the targeted system. Consequently, to … …Journal of Computer Science, Vol. 19, Issue 6 · 24 May 2023 · 5,721 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleImprovement of Rooftop Solar Panels Efficiency using Maximum Power Point Tracking Based on an Adaptive Neural Network Fuzzy Inference SystemI Made Ari Nrartha, I Made Ginarsa, Agung Budi Muljono et al.Rooftop solar panels are a strategy for achieving Indonesia's renewable energy goals, but their non-linear characteristics make them difficult to control, especially in the face of extreme weather changes. An effective controller is needed to optimize the power output of solar panels. This study proposes a Maximum Power Point Tracking (MPPT) controller based on an Adaptive Neural network Fuzzy Inference … …American Journal of Engineering and Applied Sciences, Vol. 16, Issue 1 · 19 Jan 2023 · 5,769 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Backward Regressed Capsule Neural Network for Plant Leaf Disease DetectionJennifer Jepkoech, Benson Kipkemboi Kenduiywo, David Muchangi Mugo, Edna Chebet ToolThis study investigated the introduction ofbackward regression coupled with DenseNet features in a Capsule Neural Network(CapsNet) for plant leaf disease classification. Plant diseases are consideredone of the main factors influencing food production and therefore fast cropdisease detection and recognition are important in enhancing food securityinterventions. CapsNets have successfully been adopted for plant leaf diseaseclassification however, backpropagation of signals to preceding … …Journal of Computer Science, Vol. 18, Issue 9 · 8 Sep 2022 · 5,718 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAutism Detection from 2D Transformed EEG Signal using Convolutional Neural NetworkZahrul Jannat Peya, M. A. H. Akhand, Jannatul Ferdous Srabonee, Nazmul SiddiqueAutism Spectrum Disorder (ASD) is a neurodevelopmental disorder relating to speech complications, nonverbal and social communication, and repetitive behaviors. There is no remedy for ASD but early diagnosis, mediation, and supportive care can aid the development of language, conduct, and communication skills. As the cause of ASD is a neurodevelopmental disorder, its diagnosis based on brain function analyzing different brain … …Journal of Computer Science, Vol. 18, Issue 8 · 31 Jul 2022 · 7,921 accessesView PDFCite
Research ArticleOpen accessEvery word in the titlePredicting Depression Levels using Back Propagation Neural NetworkEddy Muntina Dharma, Yaya Heryadi, Lukas et al.Depression is a mood disorder characterized by feelings of deep sadness and a sense of indifference. When depression recurs in moderate or severe intensity, it can be a serious health condition. The most effective way to deal with this problem is to predict the symptoms of depression at an early stage. In this study, a Back Propagation Neural Network (BPNN) … …Journal of Computer Science, Vol. 18, Issue 3 · 18 Mar 2022 · 6,882 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleFault-Tolerant Control of a Nonlinear Uncertain System: A Neural Network-Based Passive Approaches and Comparative Study with State-of-the-Art Control ApproachesSejal K. Raval, Himanshukumar Rajendrabhai Patel, Vipul A. ShahThis article suggests passive methods for designing Fault-Tolerant Control (FTC) for nonlinear uncertain systems with actuator and leak faults. To anticipate the Fault-Tolerant Control (FTC) action to overcome the actuator and leak faults, two-layer Feed-Forward Back-Propagation Neural Network (FFBPNN) and two-layer Cascade Forward Neural Network (CFNN) have been used, it will also tolerate external process additive disturbances. We employ the … …Journal of Computer Science, Vol. 17, Issue 7 · 3 Aug 2021 · 6,736 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleConvSVD++: A Hybrid Deep CF Recommender Model using Convolutional Neural NetworkMohamed Grida, Lamiaa Fayed, Mohamed HassanRecommender systems are powerful systems that give added value to business and corporation. They are relatively recent technology and they will only keep improving in the future. The most widely used algorithms for recommender systems are categorized into the traditional recommender and deep-based recommender system. The traditional recommendation algorithm suffers from sparse data that significantly degrades recommendation accuracy. The hybrid … …Journal of Computer Science, Vol. 16, Issue 12 · 13 Jan 2021 · 6,731 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleEfficient Implementation of Stochastic Computing Based Deep Neural Network on Low Cost Hardware with Saturation ArithmeticSunny Bodiwala, Nirali NanavatiThis study presents an efficient and rapid implementation of Stochastic Computing (SC) based Deep Neural Network (DNN) on a low-cost hardware platform. The proposed technique uses bipolar signal encoding in stochastic computing which relatively gives low hardware footprint compared to binary computing. Thereinafter, stochastic max function is presented and subsequently used to approximate the hyperbolic tangent activation function in SC. … …Journal of Computer Science, Vol. 16, Issue 11 · 17 Nov 2020 · 6,875 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleClassification Program and Story Boundaries Segmentation in TV News Broadcast Videos via Deep Convolutional Neural NetworkMounira Hmayda, Ridha Ejbali, Mourad ZaiedGiven the amount of video information on the net, the user has had difficulty finding the information in a reasonable amount of time. Thus, all video content must be segmented and annotated so that he/she can access the information directly. The goal of the proposed approach is to allow a better exploitation of video by multimedia services (TV-On- Demand, catch-up … …Journal of Computer Science, Vol. 16, Issue 5 · 14 May 2020 · 7,743 accessesView PDFCite